Comprehensive Assessment of Human Pharmacokinetic Prediction Based on In Vivo Animal Pharmacokinetic Data, Part 2: Clearance

TLDR

This is the largest publicly available data set for predicting human clearance from intravenous pharmacokinetic data in rats, dogs, and monkeys. The study demonstrates applying each prediction method to each charge class of compounds, adding a new dimension to human pharmacokinetic prediction. A comprehensive analysis of approximately 400 compounds was performed, compiling intravenous PK data from rat, dog, and monkey—including plasma protein binding and rat clearance—and comparing 37 prediction methods across diverse physicochemical properties. Methods using monkey clearance values and a model that accounts for differences in plasma protein binding between rat and human provided the best predictions, achieving about 60 % of compounds within a 2‑fold geometric mean‑fold error, while other single‑species scaling or proportionality methods incorporating the fraction unbound in the preclinical species were generally unsuccessful.

Abstract

A comprehensive analysis on the prediction of human clearance based on intravenous pharmacokinetic data from rat, dog, and monkey for approximately 400 compounds was undertaken. This data set has been carefully compiled from literature reports and expanded with some in-house determinations for plasma protein binding and rat clearance. To the authors- knowledge, this is the largest publicly available data set. The present examination offers a comparison of 37 different methods for prediction of human clearance across compounds of diverse physicochemical properties. Furthermore, this work demonstrates the application of each prediction method to each charge class of the compounds, thus presenting an additional dimension to prediction of human pharmacokinetics. In general, the observations suggest that methods employing monkey clearance values and a method incorporating differences in plasma protein binding between rat and human yield the best overall predictions as suggested by approximately 60% compounds within 2-fold geometric mean-fold error. Other single-species scaling or proportionality methods incorporating the fraction unbound in the corresponding preclinical species for prediction of free clearance in human were generally unsuccessful.